I am planning to build a chat bot using either azure framework composer, aws lex or google dialogflow but none seem to offer an easy way to have a map/location picker. It should be an straight forward interaction with user where based on a button click the user can then pick the precise location from the map.
Has anyone done something like that?
Many thanks.
I don't believe that any pure NLU framework is going to offer you that level of functionality.
The true purpose behind the likes of Amazon Lex, Google Diaglogflow is to perform intent detection and classification. It is up to the developer to build out the desired functionality associated with each of the configured intents.
What it may practically come down to is presenting the chat user with a map/location popup within the chat widget. The user could then select their current/desired location which gets sent back to the NLU framework for fulfillment.
Related
We've just published our first app in Google Workspace Marketplace (a google docs add-on) and can't figure out how, or if, it is possible to setup an email or other notification (slack notification would be cool) for our Customer Success team to be notified when a user leaves a review of the app.
Appreciate that if we get thousands we will probably turn the notifications off (or filter them in some way), at this early stage though, we're very eager to act on any feedback.
Thanks!
Disclaimer: I am creator of Obsei, and this might be biased answer.
You can try Obsei: an open-source low-code AI powered automation tool.
It can monitor App and Play stores for customer reviews and send notification Slack when someone add review there. Also Obsei can classify review contextually to classify it into issue categories. Refer below image.Obsei workflow
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Happy to answer any queries in this regards.
Can anyone offer guidance on how to call an external API from within MS Teams chat/posts initiated by an #mention or #hastag? The service I want to build would use the mention/hastag to call an API and return various types of meta data that would then be added to the chat, post, etc. Wondering if Flow or Yo Teams is the best way to go.
The best approach for this would be to create a bot, which gets a name that can be '#' mentioned (e.g. if you bot is called MyBot, you could mention #MyBot in a Teams channel, and it will get notified). Once it receives the notification, the bot can do anything you need it to do.
If you have development skills available (yourself or someone on your team), have a look at the Teams Bot development documentation to get started. If not, Power Virtual Agents could suit your needs (it's like a "drag and drop" bot creator.
I am working on a POC to proof out the ability to get a list of all the new users who have been added to a specific Slack Channel. From my initial review of the Slack API I am not seeing anything that showcases this ability, I was curious to see if anyone had worked on something similar or could point me to resources that would be a viable solution.
I believe there is no ready-made API method available, that will give you that specific information. However, Slack is very flexible and you can use the existing building blocks to easily add additional features as needed.
E.g. To get the requested information you can develop a small Slack app that listens to the member_joined_channel and member_left_channel events to keep track of when members joined a channel.
If you need a historical record of membership in a channel, you could use the Slack API's groups.history method, page through results, and build a membership log by looking for events of type member_joined_channel and member_left_channel through time.
I have a bot that uses .NET, MS Bot Framework and LUIS.ai for its smarts.
All's fine, except that I need to provide a way for non-technical users to train the bot and teach it new things, i.e. new intents in LUIS.ai.
In other words, suppose that right now the bot can answer messages like "hey bot where can i get coffee" and "where can I buy some clothes" with simple phrases containing directions. Non-technical users need to be able to train it to answer "where can I get some food" too.
Here's what I have considered:
Continuing to use LUIS.ai. Doesn't work because LUIS.ai doesn't have an API. The best it has is the GUI to refine existing intents, and the upload app/phrase list feature. The process can be semi-automated if the JSON file with the app can be generated by some application that I write; however, there still needs to be backend code that handles the new intents, and that has to be implemented by a C# coder.
Could it work if I switch from C# to Node.js? Then theoretically I would be able to auto-generate code files / intent handlers.
Azure Bot Service. Seems it doesn't have a non-technical interface and is just a browser-based IDE.
Ditching Bot Framework entirely and using third-party tools such as motion.ai. Doesn't work because there's no "intellect" as the one provided by LUIS.ai.
Using Form Flow that's part of Bot Framework. If my GUI bot builder application can generate JSON files, these files can be used by Bot Framework to build a bot automatically. Doesn't work because there's no intellect as in LUIS.ai.
Keep using Bot Framework, but ditch LUIS and build a separate web service based on a node.js language processing library for determining intents. May or may not work, may be less smart than LUIS, and could be an overkill.
Override the method in LuisDialog that selects the intent from the LuisResponse, in order to use the my own way to decide the intent (but how?).
At this point I'm out of ideas and any pointers will be greatly appreciated.
First of all, LUIS.ai provides an API that you can use to automatize the training. Moreover, here is Luis Trainer written entirely in Python against the API that just does that.
The easiest one, probably is the one you are describing in #1: you can automatize the training (as explaining above) but you will still have to deploy a new version of the bot if new intents are being provided. One thing is letting users to train an existing model with new utteraces and another completely and different thing is to let them create the model :)
It might be hard to skip having to write the backend code (I wouldn't automatize that at all)
Here is a potential idea (not sure if it will work though). You would need 2 Luis models.
One with your current model, that users will be able to train with new utterances.
The second model, is one exclusively intended to be "expanded" with new intents by users.
If you separate this in that way, you might be able to look into a "plugin" architecture for the second LUIS model. So, your app, somehow, loads dinamically an assembly where the second model lives.
Once you you have that in place, you can focus on writing the backend code for your second Luis Model without having to worry about the bot/first model. You should be able to replace the assembly with the second Luis Model and be able in the bot to detect if there is new version of that assembly and replace the current one in the app domain.
As I said, is just an idea as I'm brainstorming with you. Sounds a bit complex, and it's not addressing all your concerns; as you still will need to write code (which in any case, you will eventually have to do)
I am working through a challenge project (training) to automate the creation of Chat Bots specifically targeted against a Luis.ai model using plain old javascript and web services to Luis.
I looked at the Bot Framework and it's just too cumbersome to automate (I want X number of customers to create a Chat Bot without coding). I also want to add my own type of 'Cards' (html widgets) that do more and can be easily configured by someone with zero coding skills.
Calls to the Luis.ai/Cognitive Services API are made in my code behind and the json response returned to my own rules engine. On the following URL click the LUIS API link on the page to open the Luis API Console where you can test, and train your Model. All the endpoints you will need are here...
https://dev.projectoxford.ai/docs/services/
Based on the various endpoints on that page, you can use WebClient in asp.net to pull back the response. So in my testing I have buttons on a page to push utterances up to the model, pull back entities, create hierarchical entities and so on. Have a look at http://onlinebotbuilder.com to see how an intent of product dynamically inserted a shopping cart.
When your tool is built and utterances start to arrive, Luis.ai will store them and via the Suggest tab (at Luis.ai) it will ask you for guidance...Unfortunately I don't think you could give that control over to your customers, unless they are experts in your domain (they understand which utterance belongs to which intent). You don't need to take your app down, just train it periodically to improve the Model based on your customers input...soon enough you will have your model working well based on your intents.
Hope that helps.
I'm building a chatbot that will need to be launched on Kik, Facebook, and Slack. I'm unsure of where to start in terms of using a bot framework or whether I should create something custom myself.
I don't believe I will need any NLP. The user is going to be pushed down a very structured path, that will use buttons to guide the users to the next prompts and will also share with the user links and media.
Microsoft Bot Framework seems like the main framework I should look at, but its unclear to me how useful it will be if I end up wanting to deliver responses that are custom to each messaging platform. Meaning, on Facebook I may want to take advantage of a custom feature that they have like buttons or templates and on Kik I will want to take advantage of suggested keyboards.
Any suggestions or guidance is appreciated.
BotFramework will do the translation for you. Write to the BotFramework schema and it will using buttons for Facebook and keyboards for Kik.